MétaCan
Menu
Back to cohort
Record W4414397341 · doi:10.1108/et-01-2025-0014

Breaking the stigma: the economic returns to trades education in Canada

2025· article· en· W4414397341 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEducation + Training · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsUniversity of GuelphUniversity of Toronto
Fundersnot available
KeywordsEarningsLinkage (software)DemographicsHigher educationTrack (disk drive)Human capital

Abstract

fetched live from OpenAlex

Purpose This paper aims to document early earnings trajectories based on the educational pathways travelled by students in Ontario, Canada, with a particular focus on the outcomes of those that opt for training in the trades. Design/methodology/approach This study draws on a new administrative linkage to track the trajectories of over 61,000 students from the Toronto District School Board as they enter post-secondary education (PSE) and then the labour market. It uses regression modelling to estimate early net disparities in earnings based on PSE pathways. Findings We estimate that graduates from the “Red Seal” trades earn substantially more than counterparts emerging from college or university programs, even net of demographics and academic performance measured at the high school level. Originality/value This study is the first in Ontario, Canada, to analyse early earnings trajectories across the full spectrum of post-secondary pathways available to students. It provides useful evidence-based insights that can inform future system design and reform.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.335
Threshold uncertainty score0.939

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.039
GPT teacher head0.375
Teacher spread0.335 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it